1 | #region License Information |
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2 | /* HeuristicLab |
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3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL) |
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4 | * |
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5 | * This file is part of HeuristicLab. |
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6 | * |
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7 | * HeuristicLab is free software: you can redistribute it and/or modify |
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8 | * it under the terms of the GNU General Public License as published by |
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9 | * the Free Software Foundation, either version 3 of the License, or |
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10 | * (at your option) any later version. |
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11 | * |
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12 | * HeuristicLab is distributed in the hope that it will be useful, |
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of |
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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15 | * GNU General Public License for more details. |
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16 | * |
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17 | * You should have received a copy of the GNU General Public License |
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>. |
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19 | */ |
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20 | #endregion |
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21 | |
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22 | using System; |
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23 | using HeuristicLab.Common; |
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24 | using HeuristicLab.Core; |
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25 | using HeuristicLab.Optimization.Operators; |
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26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; |
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27 | |
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28 | namespace HeuristicLab.Encodings.IntegerVectorEncoding { |
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29 | [Item("Euclidean Similarity Calculator for IntegerVector", "Calculates the solution similarity based on the Euclidean distance and a transformation into (0;1] between two integer vectors.")] |
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30 | [StorableClass] |
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31 | public sealed class EuclideanSimilarityCalculator : SingleObjectiveSolutionSimilarityCalculator { |
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32 | protected override bool IsCommutative { |
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33 | get { return true; } |
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34 | } |
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35 | |
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36 | [Storable] |
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37 | private double scaling; |
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38 | /// <summary> |
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39 | /// The higher the scaling, the higher the similarity score for solutions of larger Euclidean distance. |
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40 | /// A value of 1 means no scaling is applied. The function for squashing the numbers into (0;1] is |
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41 | /// 1 / (1 + x / scaling) where x is the Euclidean distance. |
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42 | /// </summary> |
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43 | public double Scaling { |
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44 | get { return scaling; } |
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45 | set { scaling = value; } |
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46 | } |
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47 | |
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48 | [StorableConstructor] |
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49 | private EuclideanSimilarityCalculator(bool deserializing) : base(deserializing) { } |
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50 | private EuclideanSimilarityCalculator(EuclideanSimilarityCalculator original, Cloner cloner) |
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51 | : base(original, cloner) { |
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52 | scaling = original.scaling; |
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53 | } |
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54 | public EuclideanSimilarityCalculator() { |
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55 | scaling = 1; |
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56 | } |
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57 | |
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58 | public override IDeepCloneable Clone(Cloner cloner) { |
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59 | return new EuclideanSimilarityCalculator(this, cloner); |
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60 | } |
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61 | |
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62 | public static double CalculateSimilarity(IntegerVector left, IntegerVector right, double scaling = 1.0) { |
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63 | if (left == null || right == null) |
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64 | throw new ArgumentException("Cannot calculate similarity because one or both of the provided solutions is null."); |
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65 | if (left.Length != right.Length) |
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66 | throw new ArgumentException("Cannot calculate similarity because the provided solutions have different lengths."); |
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67 | if (left.Length == 0) |
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68 | throw new ArgumentException("Cannot calculate similarity because solutions are of length 0."); |
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69 | if (scaling <= 0) |
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70 | throw new ArgumentException("Cannot choose a 0 or negative scaling value."); |
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71 | if (ReferenceEquals(left, right)) return 1.0; |
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72 | |
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73 | var distance = 0.0; |
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74 | for (int i = 0; i < left.Length; i++) |
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75 | distance += (left[i] - right[i]) * (left[i] - right[i]); |
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76 | return 1.0 / (1.0 + Math.Sqrt(distance) / scaling); |
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77 | |
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78 | } |
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79 | |
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80 | public override double CalculateSolutionSimilarity(IScope leftSolution, IScope rightSolution) { |
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81 | var left = leftSolution.Variables[SolutionVariableName].Value as IntegerVector; |
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82 | var right = rightSolution.Variables[SolutionVariableName].Value as IntegerVector; |
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83 | |
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84 | return CalculateSimilarity(left, right, Scaling); |
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85 | } |
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86 | } |
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87 | } |
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